Women’s Health
Premenstrual symptom patterns and risk factors: a cross-sectional study of college-aged women Margaret Kucia* Margaret Kucia Ariel Scalise Aparna Tiwari Gloria DiFulvio Lynnette Sievert Tara Mandalaywala Donghao Lu Elizabeth Bertone-Johnson
Premenstrual symptoms impact over 75% of reproductive-age women and include physical, emotional, cognitive, and behavioral symptoms that occur cyclically during the luteal phase of the menstrual cycle. Approximately 13% of women miss work or school due to symptoms, and nearly 50% of women have visited a healthcare provider for menstruation concerns. Our study sought to identify latent patterns of premenstrual symptoms and to determine whether associations with risk factors varied between patterns. Our population included n=569 women aged 18–30 yrs who completed a revised version of the Calendar of Premenstrual Experiences (2022-23). Participants also provided information on body mass index, physical and mental health history, and childhood trauma. Mean age of participants was 20.3 (SD 1.7), and 67.1% self-identified as white, 5.8% as Black, 18.5% as Asian/Asian American, and 5.1% as another race. Latina ethnicity was self-reported by 8.0%. Using factor analysis we identified three distinct symptom patterns: 1) anxious, Cronbach α=0.80, symptoms with highest factor loadings (> 0.50) = dizziness, palpitations, anxiety, insomnia, confusion, and forgetfulness; 2) labile mood, Cronbach α=0.88, symptoms >0.50 = irritability, hypersensitivity, mood swings, crying easily, angry outbursts, and depression, and 3) somatic, Cronbach α=0.72, symptoms >0.50 = abdominal bloating, cramping, and back pain. Patterns were consistent with those identified in previous studies, suggesting stability across populations. Our study continues with multivariable modeling to compare how childhood trauma, body mass index, substance use, age at menarche, and hormonal birth control are associated with each of the three patterns. This analysis provides further evidence for the existence of distinct subtypes of premenstrual symptomatology. Our work will contribute to better understanding the complex etiology of symptoms, identifying risk factors, and developing tailored mitigation strategies.